{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "ba17fed4",
   "metadata": {},
   "source": [
    "这里的JSON数据出自于在线工具：[在线制作标准折线图](https://www.lddgo.net/chart/line-chart)。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "eb4ce6a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.cm as cm\n",
    "import numpy as np\n",
    "import glob\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "864e8f4b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Henan\\AppData\\Local\\Temp\\ipykernel_20216\\3414318818.py:14: MatplotlibDeprecationWarning: The get_cmap function was deprecated in Matplotlib 3.7 and will be removed in 3.11. Use ``matplotlib.colormaps[name]`` or ``matplotlib.colormaps.get_cmap()`` or ``pyplot.get_cmap()`` instead.\n",
      "  file_colors = cm.get_cmap('tab20', len(all_data))\n",
      "C:\\Users\\Henan\\AppData\\Local\\Temp\\ipykernel_20216\\3414318818.py:53: UserWarning: Glyph 36724 (\\N{CJK UNIFIED IDEOGRAPH-8F74}) missing from font(s) DejaVu Sans.\n",
      "  plt.tight_layout(rect=[0, 0, 0.85, 1])  # 为图例留出空间\n",
      "C:\\Users\\Henan\\AppData\\Local\\Temp\\ipykernel_20216\\3414318818.py:53: UserWarning: Glyph 25152 (\\N{CJK UNIFIED IDEOGRAPH-6240}) missing from font(s) DejaVu Sans.\n",
      "  plt.tight_layout(rect=[0, 0, 0.85, 1])  # 为图例留出空间\n",
      "C:\\Users\\Henan\\AppData\\Local\\Temp\\ipykernel_20216\\3414318818.py:53: UserWarning: Glyph 26377 (\\N{CJK UNIFIED IDEOGRAPH-6709}) missing from font(s) DejaVu Sans.\n",
      "  plt.tight_layout(rect=[0, 0, 0.85, 1])  # 为图例留出空间\n",
      "C:\\Users\\Henan\\AppData\\Local\\Temp\\ipykernel_20216\\3414318818.py:53: UserWarning: Glyph 25991 (\\N{CJK UNIFIED IDEOGRAPH-6587}) missing from font(s) DejaVu Sans.\n",
      "  plt.tight_layout(rect=[0, 0, 0.85, 1])  # 为图例留出空间\n",
      "C:\\Users\\Henan\\AppData\\Local\\Temp\\ipykernel_20216\\3414318818.py:53: UserWarning: Glyph 20214 (\\N{CJK UNIFIED IDEOGRAPH-4EF6}) missing from font(s) DejaVu Sans.\n",
      "  plt.tight_layout(rect=[0, 0, 0.85, 1])  # 为图例留出空间\n",
      "C:\\Users\\Henan\\AppData\\Local\\Temp\\ipykernel_20216\\3414318818.py:53: UserWarning: Glyph 21512 (\\N{CJK UNIFIED IDEOGRAPH-5408}) missing from font(s) DejaVu Sans.\n",
      "  plt.tight_layout(rect=[0, 0, 0.85, 1])  # 为图例留出空间\n",
      "C:\\Users\\Henan\\AppData\\Local\\Temp\\ipykernel_20216\\3414318818.py:53: UserWarning: Glyph 24182 (\\N{CJK UNIFIED IDEOGRAPH-5E76}) missing from font(s) DejaVu Sans.\n",
      "  plt.tight_layout(rect=[0, 0, 0.85, 1])  # 为图例留出空间\n",
      "C:\\Users\\Henan\\AppData\\Local\\Temp\\ipykernel_20216\\3414318818.py:53: UserWarning: Glyph 25240 (\\N{CJK UNIFIED IDEOGRAPH-6298}) missing from font(s) DejaVu Sans.\n",
      "  plt.tight_layout(rect=[0, 0, 0.85, 1])  # 为图例留出空间\n",
      "C:\\Users\\Henan\\AppData\\Local\\Temp\\ipykernel_20216\\3414318818.py:53: UserWarning: Glyph 32447 (\\N{CJK UNIFIED IDEOGRAPH-7EBF}) missing from font(s) DejaVu Sans.\n",
      "  plt.tight_layout(rect=[0, 0, 0.85, 1])  # 为图例留出空间\n",
      "C:\\Users\\Henan\\AppData\\Local\\Temp\\ipykernel_20216\\3414318818.py:53: UserWarning: Glyph 22270 (\\N{CJK UNIFIED IDEOGRAPH-56FE}) missing from font(s) DejaVu Sans.\n",
      "  plt.tight_layout(rect=[0, 0, 0.85, 1])  # 为图例留出空间\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_combined_lines(all_data):\n",
    "    \"\"\"在同一张图中绘制所有JSON文件的完整折线（文件级颜色区分）\"\"\"\n",
    "    plt.figure(figsize=(12, 7))\n",
    "    ax = plt.gca()\n",
    "    \n",
    "    # 颜色分配：每个文件独立颜色（tab20色板，支持最多20个文件）\n",
    "    file_colors = cm.get_cmap('tab20', len(all_data))\n",
    "    \n",
    "    for file_idx, (filename, coordinates) in enumerate(all_data):\n",
    "        if len(coordinates) < 2:\n",
    "            print(f\"跳过 {filename}：数据点不足2个\")\n",
    "            continue\n",
    "        \n",
    "        x = [p['x'] for p in coordinates]\n",
    "        y = [p['y'] for p in coordinates]\n",
    "        color = file_colors(file_idx)\n",
    "        \n",
    "        # 绘制完整折线\n",
    "        ax.plot(x, y, color=color, marker='o', markersize=6, \n",
    "               linewidth=2, alpha=0.9, label=filename)\n",
    "        \n",
    "        # 标注点（每5个点或首尾点，显示文件内序号）\n",
    "        for i, (px, py) in enumerate(zip(x, y)):\n",
    "            if i % 5 == 0 or i == len(coordinates)-1:\n",
    "                ax.text(px, py, f'{i+1}', fontsize=8,\n",
    "                       color=color, ha='center', va='bottom',\n",
    "                       bbox=dict(facecolor='white', alpha=0.7, edgecolor='none'))\n",
    "\n",
    "    # 图表设置\n",
    "    ax.set_title(\"所有JSON文件合并折线图\", fontsize=14)\n",
    "    ax.set_xlabel(\"X轴\", fontsize=12)\n",
    "    ax.set_ylabel(\"Y轴\", fontsize=12)\n",
    "    ax.grid(True, linestyle='--', alpha=0.6)\n",
    "    \n",
    "    # 自动范围\n",
    "    all_x = [p['x'] for _, coords in all_data for p in coords]\n",
    "    all_y = [p['y'] for _, coords in all_data for p in coords]\n",
    "    if all_x:\n",
    "        ax.set_xlim(min(all_x)-0.1, max(all_x)+0.1)\n",
    "        ax.set_ylim(min(all_y)-0.1, max(all_y)+0.1)\n",
    "    \n",
    "    # 图例优化（右侧独立区域）\n",
    "    ax.legend(loc='upper left', bbox_to_anchor=(1, 1), title='文件',\n",
    "             framealpha=0.9, handlelength=1.5, columnspacing=1)\n",
    "    \n",
    "    plt.tight_layout(rect=[0, 0, 0.85, 1])  # 为图例留出空间\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8d81faa0",
   "metadata": {},
   "outputs": [],
   "source": [
    "def process_all_json():\n",
    "    \"\"\"处理当前目录下所有JSON文件并合并绘图\"\"\"\n",
    "    json_files = glob.glob(os.path.join(os.getcwd(), '*.json'))\n",
    "    all_data = []\n",
    "    \n",
    "    if not json_files:\n",
    "        print(\"当前目录下没有找到JSON文件\")\n",
    "        return\n",
    "    \n",
    "    for file_path in json_files:\n",
    "        try:\n",
    "            with open(file_path, 'r') as f:\n",
    "                data = json.load(f)\n",
    "            coords = data.get('coordinates', [])\n",
    "            if not isinstance(coords, list) or len(coords) < 2:\n",
    "                raise ValueError(f\"需要至少2个坐标点（文件：{file_path}）\")\n",
    "            all_data.append((os.path.basename(file_path), coords))\n",
    "        except Exception as e:\n",
    "            print(f\"跳过 {file_path}：{str(e)}\")\n",
    "            continue\n",
    "    \n",
    "    if all_data:\n",
    "        plot_combined_lines(all_data)\n",
    "    else:\n",
    "        print(\"没有有效数据可以绘制\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ac6ae6df",
   "metadata": {},
   "outputs": [],
   "source": [
    "if __name__ == \"__main__\":\n",
    "    process_all_json()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
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